{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting MySQL\n",
      "  Downloading mysql-0.0.3-py3-none-any.whl.metadata (746 bytes)\n",
      "Collecting mysqlclient (from MySQL)\n",
      "  Downloading mysqlclient-2.2.7-cp313-cp313-win_amd64.whl.metadata (4.8 kB)\n",
      "Downloading mysql-0.0.3-py3-none-any.whl (1.2 kB)\n",
      "Downloading mysqlclient-2.2.7-cp313-cp313-win_amd64.whl (208 kB)\n",
      "Installing collected packages: mysqlclient, MySQL\n",
      "Successfully installed MySQL-0.0.3 mysqlclient-2.2.7\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 24.2 -> 24.3.1\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "%pip install MySQL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 24.2 -> 24.3.1\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: numpy in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (2.1.3)\n"
     ]
    }
   ],
   "source": [
    "pip install numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (2.2.3)\n",
      "Requirement already satisfied: numpy>=1.26.0 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from pandas) (2.1.3)\n",
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      "Requirement already satisfied: six>=1.5 in c:\\users\\lenovo\\appdata\\roaming\\python\\python313\\site-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 24.2 -> 24.3.1\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "pip install pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: tushare in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (1.4.14)\n",
      "Requirement already satisfied: pandas in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from tushare) (2.2.3)\n",
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      "Requirement already satisfied: numpy>=1.26.0 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from pandas->tushare) (2.1.3)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in c:\\users\\lenovo\\appdata\\roaming\\python\\python313\\site-packages (from pandas->tushare) (2.9.0.post0)\n",
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      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from requests->tushare) (2024.12.14)\n",
      "Requirement already satisfied: colorama in c:\\users\\lenovo\\appdata\\roaming\\python\\python313\\site-packages (from tqdm->tushare) (0.4.6)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\lenovo\\appdata\\roaming\\python\\python313\\site-packages (from python-dateutil>=2.8.2->pandas->tushare) (1.16.0)\n",
      "Requirement already satisfied: soupsieve>1.2 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from beautifulsoup4->bs4->tushare) (2.6)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 24.2 -> 24.3.1\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "pip install tushare"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: matplotlib in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (3.9.3)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib) (1.3.1)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib) (4.55.2)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib) (1.4.7)\n",
      "Requirement already satisfied: numpy>=1.23 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib) (2.1.3)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\users\\lenovo\\appdata\\roaming\\python\\python313\\site-packages (from matplotlib) (24.2)\n",
      "Requirement already satisfied: pillow>=8 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib) (11.0.0)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib) (3.2.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\lenovo\\appdata\\roaming\\python\\python313\\site-packages (from matplotlib) (2.9.0.post0)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\lenovo\\appdata\\roaming\\python\\python313\\site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 24.2 -> 24.3.1\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "pip install matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting sqlalchemy\n",
      "  Downloading SQLAlchemy-2.0.37-cp313-cp313-win_amd64.whl.metadata (9.9 kB)\n",
      "Collecting greenlet!=0.4.17 (from sqlalchemy)\n",
      "  Downloading greenlet-3.1.1-cp313-cp313-win_amd64.whl.metadata (3.9 kB)\n",
      "Collecting typing-extensions>=4.6.0 (from sqlalchemy)\n",
      "  Using cached typing_extensions-4.12.2-py3-none-any.whl.metadata (3.0 kB)\n",
      "Downloading SQLAlchemy-2.0.37-cp313-cp313-win_amd64.whl (2.1 MB)\n",
      "   ---------------------------------------- 0.0/2.1 MB ? eta -:--:--\n",
      "   ---------------------------------------- 0.0/2.1 MB ? eta -:--:--\n",
      "   ----- ---------------------------------- 0.3/2.1 MB ? eta -:--:--\n",
      "   -------------------- ------------------- 1.0/2.1 MB 2.9 MB/s eta 0:00:01\n",
      "   ---------------------------------------- 2.1/2.1 MB 4.3 MB/s eta 0:00:00\n",
      "Downloading greenlet-3.1.1-cp313-cp313-win_amd64.whl (299 kB)\n",
      "Using cached typing_extensions-4.12.2-py3-none-any.whl (37 kB)\n",
      "Installing collected packages: typing-extensions, greenlet, sqlalchemy\n",
      "Successfully installed greenlet-3.1.1 sqlalchemy-2.0.37 typing-extensions-4.12.2\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 24.2 -> 24.3.1\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "pip install sqlalchemy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import tushare as ts\n",
    "import MySQLdb as mdb\n",
    "\n",
    "import matplotlib\n",
    "matplotlib.use('TkAgg')\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from matplotlib.collections import LineCollection\n",
    "\n",
    "from sklearn import cluster,covariance,manifold\n",
    "\n",
    "from sqlalchemy import create_engine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "pro = ts.pro_api(\"0e2cf9a4a2125c99a96f0dc61f97757f1380fe40c6f50b125aea60c5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:2: SyntaxWarning: invalid escape sequence '\\P'\n",
      "<>:2: SyntaxWarning: invalid escape sequence '\\P'\n",
      "C:\\Users\\lenovo\\AppData\\Local\\Temp\\ipykernel_56680\\1287086052.py:2: SyntaxWarning: invalid escape sequence '\\P'\n",
      "  sys.path.append(\"C:\\Program Files\\Python310\\Lib\\site-packages\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        ts_code trade_date   open   high    low  close  pre_close  change  \\\n",
      "0     920128.BJ   20250124  28.35  28.35  27.70  27.80      27.94   -0.14   \n",
      "1     920118.BJ   20250124  24.10  24.59  24.01  24.42      24.29    0.13   \n",
      "2     920116.BJ   20250124  48.00  48.75  47.03  47.80      48.25   -0.45   \n",
      "3     920111.BJ   20250124  24.09  24.87  24.09  24.47      24.55   -0.08   \n",
      "4     920106.BJ   20250124  56.49  58.37  56.25  57.18      55.20    1.98   \n",
      "...         ...        ...    ...    ...    ...    ...        ...     ...   \n",
      "5995  688244.SH   20250123  27.50  27.50  25.03  25.03      27.60   -2.57   \n",
      "5996  688239.SH   20250123  42.18  42.89  41.70  42.05      42.35   -0.30   \n",
      "5997  688238.SH   20250123   4.62   4.69   4.56   4.57       4.58   -0.01   \n",
      "5998  688237.SH   20250123  22.07  22.70  22.01  22.12      22.04    0.08   \n",
      "5999  688236.SH   20250123  11.75  11.88  11.65  11.67      11.65    0.02   \n",
      "\n",
      "      pct_chg       vol      amount  \n",
      "0     -0.5011   6781.63   18964.081  \n",
      "1      0.5352   1835.70    4476.014  \n",
      "2     -0.9326  44587.15  212700.177  \n",
      "3     -0.3259  18705.00   45877.959  \n",
      "4      3.5870  11257.92   64668.158  \n",
      "...       ...       ...         ...  \n",
      "5995  -9.3116  38866.22  101725.871  \n",
      "5996  -0.7084  45896.07  194526.692  \n",
      "5997  -0.2183  67083.12   31159.039  \n",
      "5998   0.3630   7334.50   16382.255  \n",
      "5999   0.1717  11154.25   13117.054  \n",
      "\n",
      "[6000 rows x 11 columns]\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "sys.path.append(\"C:\\Program Files\\Python310\\Lib\\site-packages\")\n",
    "import tushare as ts\n",
    "\n",
    "\n",
    "ts.set_token('0e2cf9a4a2125c99a96f0dc61f97757f1380fe40c6f50b125aea60c5')\n",
    "pro = ts.pro_api()\n",
    "\n",
    "params = {\n",
    "    \"ts_code\": \"601939.SH\",\n",
    "    \"trade_date\": \"\",\n",
    "    \"start_date\": 20100101,\n",
    "    \"end_date\": 20241225,\n",
    "    \"offset\": \"\",\n",
    "    \"limit\": \"\",\n",
    "    \"fields\": [\n",
    "        \"ts_code\",\n",
    "        \"trade_date\",\n",
    "        \"open\",\n",
    "        \"high\",\n",
    "        \"low\",\n",
    "        \"close\",\n",
    "        \"pre_close\",\n",
    "        \"change\",\n",
    "        \"pct_close\",\n",
    "        \"change\",\n",
    "        \"pct_chg\",\n",
    "        \"vol\",\n",
    "        \"amount\"\n",
    "    ]\n",
    "}\n",
    "df = pro.daily(params)\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting mplfinance\n",
      "  Downloading mplfinance-0.12.10b0-py3-none-any.whl.metadata (19 kB)\n",
      "Requirement already satisfied: matplotlib in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from mplfinance) (3.9.3)\n",
      "Requirement already satisfied: pandas in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from mplfinance) (2.2.3)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib->mplfinance) (1.3.1)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib->mplfinance) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib->mplfinance) (4.55.2)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib->mplfinance) (1.4.7)\n",
      "Requirement already satisfied: numpy>=1.23 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib->mplfinance) (2.1.3)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\users\\lenovo\\appdata\\roaming\\python\\python313\\site-packages (from matplotlib->mplfinance) (24.2)\n",
      "Requirement already satisfied: pillow>=8 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib->mplfinance) (11.0.0)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from matplotlib->mplfinance) (3.2.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\lenovo\\appdata\\roaming\\python\\python313\\site-packages (from matplotlib->mplfinance) (2.9.0.post0)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from pandas->mplfinance) (2024.2)\n",
      "Requirement already satisfied: tzdata>=2022.7 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from pandas->mplfinance) (2024.2)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\lenovo\\appdata\\roaming\\python\\python313\\site-packages (from python-dateutil>=2.7->matplotlib->mplfinance) (1.16.0)\n",
      "Downloading mplfinance-0.12.10b0-py3-none-any.whl (75 kB)\n",
      "Installing collected packages: mplfinance\n",
      "Successfully installed mplfinance-0.12.10b0\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 24.2 -> 24.3.1\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "pip install mplfinance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import mplfinance as mpf\n",
    "\n",
    "# 生成模拟数据的代码保持不变\n",
    "\n",
    "# 创建DataFrame\n",
    "data = pd.DataFrame({\n",
    "    'Open': open_prices,\n",
    "    'High': high_prices,\n",
    "    'Low': low_prices,\n",
    "    'Close': close_prices\n",
    "}, index=dates)\n",
    "\n",
    "# 绘制蜡烛图\n",
    "mpf.plot(data, type='candle', style='yahoo', figsize=(12, 6))\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "# 在绘制图表后添加以下代码\n",
    "ax.xaxis.set_major_locator(mdates.DayLocator(interval=10))  # 每10天显示一个刻度\n",
    "ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x575 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import mplfinance as mpf\n",
    "\n",
    "# 手动创建包含多日数据的数据帧\n",
    "data = {\n",
    "    'ts_code': ['920128.BJ'] * 5 + ['920118.BJ'] * 5,\n",
    "    'trade_date': ['20250120', '20250121', '20250122', '20250123', '20250124'] * 2,\n",
    "    'open': [28.0, 28.2, 28.3, 28.35, 28.35, 24.0, 24.1, 24.15, 24.10, 24.10],\n",
    "    'high': [28.2, 28.4, 28.5, 28.35, 28.35, 24.2, 24.4, 24.5, 24.59, 24.59],\n",
    "    'low': [27.8, 27.9, 27.75, 27.70, 27.70, 23.9, 24.0, 24.05, 24.01, 24.01],\n",
    "    'close': [28.1, 28.3, 28.2, 27.80, 27.80, 24.1, 24.2, 24.3, 24.42, 24.42],\n",
    "    'pre_close': [27.9, 28.1, 28.3, 28.2, 27.94, 23.9, 24.1, 24.2, 24.3, 24.29],\n",
    "    'change': [0.2, 0.2, -0.1, -0.4, -0.14, 0.2, 0.1, 0.1, 0.12, 0.13],\n",
    "    'pct_chg': [0.7168, 0.7117, -0.3534, -1.4286, -0.5011, 0.8368, 0.4149, 0.4132, 0.4938, 0.5352],\n",
    "    'vol': [6000, 6200, 6500, 6781.63, 6781.63, 1500, 1600, 1700, 1835.70, 1835.70],\n",
    "    'amount': [17000, 17500, 18000, 18964.081, 18964.081, 3500, 3800, 4000, 4476.014, 4476.014]\n",
    "}\n",
    "\n",
    "# 将数据转换为DataFrame，并设置trade_date为索引\n",
    "df = pd.DataFrame(data)\n",
    "df['trade_date'] = pd.to_datetime(df['trade_date'])\n",
    "df.set_index('trade_date', inplace=True)\n",
    "\n",
    "# 选择其中一个股票的数据\n",
    "single_stock_df = df[df['ts_code'] == '920128.BJ'].drop(columns=['ts_code'])\n",
    "\n",
    "# 绘制K线图（不绘制交易量图）\n",
    "mpf.plot(single_stock_df, type='candle', style='charles', title='Stock Price Candlestick Chart for 920128.BJ', ylabel='Price')\n",
    "# 绘制K线图，添加5日和10日均线，并调整图表大小\n",
    "mpf.plot(single_stock_df, type='candle', style='charles', title='Stock Price Candlestick Chart for 920128.BJ',\n",
    "         ylabel='Price', mav=(5, 10), figsize=(12, 6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting pymysql\n",
      "  Using cached PyMySQL-1.1.1-py3-none-any.whl.metadata (4.4 kB)\n",
      "Using cached PyMySQL-1.1.1-py3-none-any.whl (44 kB)\n",
      "Installing collected packages: pymysql\n",
      "Successfully installed pymysql-1.1.1\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 24.2 -> 24.3.1\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "pip install pymysql"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting cryptography\n",
      "  Downloading cryptography-44.0.0-cp39-abi3-win_amd64.whl.metadata (5.7 kB)\n",
      "Collecting cffi>=1.12 (from cryptography)\n",
      "  Downloading cffi-1.17.1-cp313-cp313-win_amd64.whl.metadata (1.6 kB)\n",
      "Collecting pycparser (from cffi>=1.12->cryptography)\n",
      "  Downloading pycparser-2.22-py3-none-any.whl.metadata (943 bytes)\n",
      "Downloading cryptography-44.0.0-cp39-abi3-win_amd64.whl (3.2 MB)\n",
      "   ---------------------------------------- 0.0/3.2 MB ? eta -:--:--\n",
      "   ---------------------------------------- 0.0/3.2 MB ? eta -:--:--\n",
      "   --- ------------------------------------ 0.3/3.2 MB ? eta -:--:--\n",
      "   ---------------- ----------------------- 1.3/3.2 MB 3.5 MB/s eta 0:00:01\n",
      "   ------------------------------------ --- 2.9/3.2 MB 5.0 MB/s eta 0:00:01\n",
      "   ---------------------------------------- 3.2/3.2 MB 4.8 MB/s eta 0:00:00\n",
      "Downloading cffi-1.17.1-cp313-cp313-win_amd64.whl (182 kB)\n",
      "Downloading pycparser-2.22-py3-none-any.whl (117 kB)\n",
      "Installing collected packages: pycparser, cffi, cryptography\n",
      "Successfully installed cffi-1.17.1 cryptography-44.0.0 pycparser-2.22\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 24.2 -> 24.3.1\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "pip install cryptography"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "写入数据库时发生错误: (pymysql.err.OperationalError) (1045, \"Access denied for user 'root'@'localhost' (using password: YES)\")\n",
      "(Background on this error at: https://sqlalche.me/e/20/e3q8)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sqlalchemy import create_engine\n",
    "\n",
    "data_list = [\n",
    "    {'ts_code': '920128.BJ', 'trade_date': '20250124', 'open': 28.35, 'high': 28.35, 'low': 27.70, 'close': 27.80, 'pre_close': 27.94, 'change': -0.14, 'pct_chg': -0.5011, 'vol': 6781.63, 'amount': 18964.081}\n",
    "]\n",
    "df = pd.DataFrame(data_list)\n",
    "df['trade_date'] = pd.to_datetime(df['trade_date'])\n",
    "\n",
    "try:\n",
    "    # 请确保这里的用户名、密码和数据库名正确\n",
    "    engine = create_engine('mysql+pymysql://root:wxyKF2004@localhost/stock_data')\n",
    "    df.to_sql('stock_basic', con=engine, if_exists='replace', index=False)\n",
    "    print(\"数据成功写入数据库。\")\n",
    "except Exception as e:\n",
    "    print(f\"写入数据库时发生错误: {e}\")\n",
    "finally:\n",
    "    if 'engine' in locals():\n",
    "        engine.dispose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       ts_code trade_date   open   high    low  close  pre_close  change  \\\n",
      "0    000001.SZ   20241231  11.93  11.99  11.70  11.70      11.95   -0.25   \n",
      "1    000001.SZ   20241230  11.78  11.97  11.78  11.95      11.83    0.12   \n",
      "2    000001.SZ   20241227  11.87  11.90  11.66  11.83      11.86   -0.03   \n",
      "3    000001.SZ   20241226  11.92  11.93  11.78  11.86      11.92   -0.06   \n",
      "4    000001.SZ   20241225  11.86  12.02  11.84  11.92      11.86    0.06   \n",
      "..         ...        ...    ...    ...    ...    ...        ...     ...   \n",
      "237  000001.SZ   20240108   9.23   9.30   9.11   9.15       9.27   -0.12   \n",
      "238  000001.SZ   20240105   9.10   9.44   9.07   9.27       9.11    0.16   \n",
      "239  000001.SZ   20240104   9.19   9.19   9.08   9.11       9.20   -0.09   \n",
      "240  000001.SZ   20240103   9.19   9.22   9.15   9.20       9.21   -0.01   \n",
      "241  000001.SZ   20240102   9.39   9.42   9.21   9.21       9.39   -0.18   \n",
      "\n",
      "     pct_chg         vol       amount  \n",
      "0    -2.0921  1475367.33  1747242.074  \n",
      "1     1.0144  1351846.36  1610892.096  \n",
      "2    -0.2530  1290012.28  1518383.345  \n",
      "3    -0.5034  1000074.70  1183745.519  \n",
      "4     0.5059  1475282.94  1759956.630  \n",
      "..       ...         ...          ...  \n",
      "237  -1.2945  1121156.19  1029006.549  \n",
      "238   1.7563  1991622.16  1852659.692  \n",
      "239  -0.9783   864193.99   787470.082  \n",
      "240  -0.1086   733610.31   673673.614  \n",
      "241  -1.9169  1158366.45  1075742.252  \n",
      "\n",
      "[242 rows x 11 columns]\n"
     ]
    }
   ],
   "source": [
    "import tushare as ts\n",
    "\n",
    "# 初始化 Pro API 对象\n",
    "pro = ts.pro_api('0e2cf9a4a2125c99a96f0dc61f97757f1380fe40c6f50b125aea60c5')\n",
    "\n",
    "# 调用接口获取数据，这里以获取每日行情数据为例\n",
    "df = pro.daily(ts_code='000001.SZ', start_date='20240101', end_date='20241231')\n",
    "\n",
    "# 打印获取到的数据\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5395 entries, 0 to 5394\n",
      "Data columns (total 10 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   ts_code       5395 non-null   object\n",
      " 1   symbol        5395 non-null   object\n",
      " 2   name          5395 non-null   object\n",
      " 3   area          5380 non-null   object\n",
      " 4   industry      5380 non-null   object\n",
      " 5   cnspell       5395 non-null   object\n",
      " 6   market        5395 non-null   object\n",
      " 7   list_date     5395 non-null   object\n",
      " 8   act_name      2575 non-null   object\n",
      " 9   act_ent_type  2575 non-null   object\n",
      "dtypes: object(10)\n",
      "memory usage: 421.6+ KB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.count of         ts_code  symbol     name  area industry cnspell market list_date  \\\n",
       "0     000001.SZ  000001     平安银行    深圳       银行    payh     主板  19910403   \n",
       "1     000002.SZ  000002      万科A    深圳     全国地产     wka     主板  19910129   \n",
       "2     000004.SZ  000004     国华网安    深圳     软件服务    ghwa     主板  19910114   \n",
       "3     000006.SZ  000006     深振业A    深圳     区域地产    szya     主板  19920427   \n",
       "4     000007.SZ  000007      全新好    深圳     其他商业     qxh     主板  19920413   \n",
       "...         ...     ...      ...   ...      ...     ...    ...       ...   \n",
       "5390  920111.BJ  920111     聚星科技  None     None    jxkj    北交所  20241111   \n",
       "5391  920116.BJ  920116     星图测控  None     None    xtck    北交所  20250102   \n",
       "5392  920118.BJ  920118     太湖远大  None     None    thyd    北交所  20240822   \n",
       "5393  920128.BJ  920128     胜业电气  None     None    sydq    北交所  20241129   \n",
       "5394  689009.SH  689009  九号公司-WD    北京      摩托车    jhgs    科创板  20201029   \n",
       "\n",
       "                act_name act_ent_type  \n",
       "0                 无实际控制人            无  \n",
       "1     深圳市人民政府国有资产监督管理委员会         地方国企  \n",
       "2                    李映彤         民营企业  \n",
       "3     深圳市人民政府国有资产监督管理委员会         地方国企  \n",
       "4                    王玩虹         民营企业  \n",
       "...                  ...          ...  \n",
       "5390                None         None  \n",
       "5391                None         None  \n",
       "5392                None         None  \n",
       "5393                None         None  \n",
       "5394                None         None  \n",
       "\n",
       "[5395 rows x 10 columns]>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pro.query('stock_basic',exchange='',list_status='L')\n",
    "data.info()\n",
    "data.count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20215 (\\N{CJK UNIFIED IDEOGRAPH-4EF7}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26684 (\\N{CJK UNIFIED IDEOGRAPH-683C}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 22797 (\\N{CJK UNIFIED IDEOGRAPH-590D}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26434 (\\N{CJK UNIFIED IDEOGRAPH-6742}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 30340 (\\N{CJK UNIFIED IDEOGRAPH-7684}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 37329 (\\N{CJK UNIFIED IDEOGRAPH-91D1}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 34701 (\\N{CJK UNIFIED IDEOGRAPH-878D}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20998 (\\N{CJK UNIFIED IDEOGRAPH-5206}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26512 (\\N{CJK UNIFIED IDEOGRAPH-6790}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 22270 (\\N{CJK UNIFIED IDEOGRAPH-56FE}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 34920 (\\N{CJK UNIFIED IDEOGRAPH-8868}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 900x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import mplfinance as mpf\n",
    "\n",
    "# 设置随机种子以保证结果可复现\n",
    "np.random.seed(0)\n",
    "\n",
    "# 生成日期范围\n",
    "dates = pd.date_range(start='2024-01-20', periods=100, freq='B')\n",
    "\n",
    "# 生成模拟的 K 线数据\n",
    "data = {\n",
    "    'Open': np.random.uniform(100, 200, size=len(dates)),\n",
    "    'High': np.random.uniform(105, 205, size=len(dates)),\n",
    "    'Low': np.random.uniform(95, 195, size=len(dates)),\n",
    "    'Close': np.random.uniform(100, 200, size=len(dates)),\n",
    "    'Volume': np.random.uniform(5000, 15000, size=len(dates)).astype(int)\n",
    "}\n",
    "\n",
    "# 创建 DataFrame\n",
    "df = pd.DataFrame(data, index=dates)\n",
    "\n",
    "# 计算 50 日和 200 日移动平均线\n",
    "df['MA_50'] = df['Close'].rolling(window=50).mean()\n",
    "df['MA_200'] = df['Close'].rolling(window=200).mean()\n",
    "\n",
    "# 计算相对强弱指数（RSI）\n",
    "delta = df['Close'].diff()\n",
    "gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()\n",
    "loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()\n",
    "rs = gain / loss.replace(0, np.nan)  # 避免除以零\n",
    "rs = rs.fillna(1)  # 用 1 填充 NaN 值，以避免计算错误\n",
    "df['RSI'] = 100 - (100 / (1 + rs))\n",
    "\n",
    "# 创建自定义的 mpf_style 对象来定义图表的样式\n",
    "mpf_style = mpf.make_mpf_style(base_mpf_style='charles', rc={'font.size': 8})\n",
    "\n",
    "# 定义额外的绘图对象\n",
    "apds = [\n",
    "    mpf.make_addplot(df['MA_50'], color='blue', secondary_y=False),\n",
    "    mpf.make_addplot(df['MA_200'], color='red', secondary_y=False),\n",
    "    mpf.make_addplot(df['RSI'], type='line', panel=1, color='green', secondary_y=True, ylabel='RSI')\n",
    "]\n",
    "\n",
    "# 定义绘图参数\n",
    "plot_kwargs = {\n",
    "    'type': 'candle',\n",
    "    'style': mpf_style,\n",
    "    'title': '复杂的金融分析图表',\n",
    "    'ylabel': '价格',\n",
    "    'volume': True,\n",
    "    'addplot': apds,\n",
    "    'panel_ratios': (6, 2),  # 调整主图和副图的比例\n",
    "    'figsize': (9, 6),  # 调整整个图表的大小\n",
    "    'show_nontrading': False  # 不显示非交易日\n",
    "}\n",
    "\n",
    "# 绘制图表\n",
    "mpf.plot(df, **plot_kwargs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: django in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (5.1.5)\n",
      "Requirement already satisfied: asgiref<4,>=3.8.1 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from django) (3.8.1)\n",
      "Requirement already satisfied: sqlparse>=0.3.1 in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from django) (0.5.3)\n",
      "Requirement already satisfied: tzdata in c:\\users\\lenovo\\appdata\\local\\programs\\python\\python313\\lib\\site-packages (from django) (2024.2)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "[notice] A new release of pip is available: 24.2 -> 24.3.1\n",
      "[notice] To update, run: python.exe -m pip install --upgrade pip\n"
     ]
    }
   ],
   "source": [
    "%pip install django"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 24179 (\\N{CJK UNIFIED IDEOGRAPH-5E73}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 23433 (\\N{CJK UNIFIED IDEOGRAPH-5B89}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 38134 (\\N{CJK UNIFIED IDEOGRAPH-94F6}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 34892 (\\N{CJK UNIFIED IDEOGRAPH-884C}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20013 (\\N{CJK UNIFIED IDEOGRAPH-4E2D}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20852 (\\N{CJK UNIFIED IDEOGRAPH-5174}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 36890 (\\N{CJK UNIFIED IDEOGRAPH-901A}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 35759 (\\N{CJK UNIFIED IDEOGRAPH-8BAF}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 25910 (\\N{CJK UNIFIED IDEOGRAPH-6536}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 30424 (\\N{CJK UNIFIED IDEOGRAPH-76D8}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20215 (\\N{CJK UNIFIED IDEOGRAPH-4EF7}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26684 (\\N{CJK UNIFIED IDEOGRAPH-683C}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21147 (\\N{CJK UNIFIED IDEOGRAPH-529B}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 30005 (\\N{CJK UNIFIED IDEOGRAPH-7535}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 22120 (\\N{CJK UNIFIED IDEOGRAPH-5668}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import io\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib as mpl\n",
    "\n",
    "# 设置全局字体大小\n",
    "mpl.rcParams['font.size'] = 8\n",
    "\n",
    "\n",
    "data = \"\"\"\n",
    "trade_date,ts_code,name,close,change,rank,market_type,amount,net_amount,buy,sell\n",
    "20240101,000001.SZ,平安银行,15.2,0.2,5,1,250000000.0,30000000.0,140000000.0,110000000.0\n",
    "20240101,000063.SZ,中兴通讯,32.5,0.5,3,1,350000000.0,50000000.0,200000000.0,150000000.0\n",
    "20240101,000651.SZ,格力电器,38.8,-0.3,6,1,280000000.0,-20000000.0,130000000.0,150000000.0\n",
    "20240102,000001.SZ,平安银行,15.3,0.1,4,1,260000000.0,35000000.0,145000000.0,115000000.0\n",
    "20240102,000063.SZ,中兴通讯,33.0,0.5,2,1,360000000.0,55000000.0,205000000.0,155000000.0\n",
    "20240102,000651.SZ,格力电器,38.6,-0.2,7,1,270000000.0,-15000000.0,127500000.0,142500000.0\n",
    "20240103,000001.SZ,平安银行,15.4,0.1,3,1,270000000.0,40000000.0,155000000.0,120000000.0\n",
    "20240103,000063.SZ,中兴通讯,33.5,0.5,1,1,370000000.0,60000000.0,215000000.0,160000000.0\n",
    "20240103,000651.SZ,格力电器,38.5,-0.1,8,1,265000000.0,-10000000.0,127500000.0,137500000.0\n",
    "\"\"\"\n",
    "\n",
    "# 使用 io.StringIO 来加载数据\n",
    "data_stream = io.StringIO(data)\n",
    "df = pd.read_csv(data_stream)\n",
    "\n",
    "# 将 trade_date 列转换为日期格式\n",
    "df['trade_date'] = pd.to_datetime(df['trade_date'], format='%Y%m%d')\n",
    "\n",
    "# 设置绘图风格（可选）\n",
    "plt.style.use('ggplot')\n",
    "\n",
    "# 创建一个图形和多个子图，调整 figsize 以适应更小的子图\n",
    "fig, axes = plt.subplots(nrows=len(df['ts_code'].unique()), figsize=(8, len(df['ts_code'].unique()) * 2), sharex=True)\n",
    "\n",
    "# 处理只有一个子图的情况\n",
    "if isinstance(axes, plt.Axes):\n",
    "    axes = [axes]\n",
    "\n",
    "# 绘制每个股票的收盘价\n",
    "for ax, (ts_code, group) in zip(axes, df.groupby('ts_code')):\n",
    "    ax.plot(group['trade_date'], group['close'], marker='o', label=group['name'].iloc[0] if ax == axes[0] else None)  # 只在第一个子图上显示图例\n",
    "    ax.set_title(group['name'].iloc[0], fontsize=9)  # 调整标题字体大小\n",
    "    ax.set_ylabel('收盘价', fontsize=9)  # 调整 y 轴标签字体大小\n",
    "    ax.grid(True, which='both', linestyle='--', linewidth=0.5)  # 自定义网格线样式\n",
    "    ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
    "    ax.xaxis.set_major_locator(mdates.DayLocator())\n",
    "    ax.tick_params(axis='both', which='major', labelsize=8)  # 调整刻度标签字体大小\n",
    "\n",
    "# 隐藏除了最后一个子图之外的所有子图的 x 轴刻度标签和 y 轴标签（除了第一个）\n",
    "for ax in axes[:-1]:\n",
    "    ax.set_xticklabels([])\n",
    "    ax.set_ylabel('')  # 隐藏 y 轴标签（除了第一个子图）\n",
    "\n",
    "# 只在最后一个子图上显示 x 轴标签\n",
    "axes[-1].xaxis.set_tick_params(labelbottom=True)\n",
    "\n",
    "# 调整子图之间的间距\n",
    "plt.subplots_adjust(hspace=0.3, wspace=0)\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20215 (\\N{CJK UNIFIED IDEOGRAPH-4EF7}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26684 (\\N{CJK UNIFIED IDEOGRAPH-683C}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 32929 (\\N{CJK UNIFIED IDEOGRAPH-80A1}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 31080 (\\N{CJK UNIFIED IDEOGRAPH-7968}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 36208 (\\N{CJK UNIFIED IDEOGRAPH-8D70}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 21183 (\\N{CJK UNIFIED IDEOGRAPH-52BF}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 22270 (\\N{CJK UNIFIED IDEOGRAPH-56FE}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 20132 (\\N{CJK UNIFIED IDEOGRAPH-4EA4}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26131 (\\N{CJK UNIFIED IDEOGRAPH-6613}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26085 (\\N{CJK UNIFIED IDEOGRAPH-65E5}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 26399 (\\N{CJK UNIFIED IDEOGRAPH-671F}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 25910 (\\N{CJK UNIFIED IDEOGRAPH-6536}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 30424 (\\N{CJK UNIFIED IDEOGRAPH-76D8}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "C:\\Users\\lenovo\\AppData\\Roaming\\Python\\Python313\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Glyph 24320 (\\N{CJK UNIFIED IDEOGRAPH-5F00}) missing from font(s) DejaVu Sans.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "data = {\n",
    "    'ts_code': ['600519.SH'] * 10,\n",
    "    'trade_date': pd.to_datetime(['20230101', '20230201', '20230301', '20230401', '20230501',\n",
    "                                  '20230601', '20230701', '20230801', '20230901', '20231001']),\n",
    "    'close': [1700, 1750, 1800, 1780, 1820, 1850, 1830, 1860, 1880, 1900],\n",
    "    'open': [1690, 1740, 1790, 1770, 1810, 1840, 1820, 1850, 1870, 1890],\n",
    "    'high': [1720, 1770, 1820, 1800, 1840, 1870, 1850, 1880, 1900, 1920],\n",
    "    'low': [1680, 1730, 1780, 1760, 1800, 1830, 1810, 1840, 1860, 1880]\n",
    "}\n",
    "\n",
    "# 创建DataFrame\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# 按日期升序排序\n",
    "df = df.sort_values(by='trade_date')\n",
    "\n",
    "# 设置绘图风格（可选）\n",
    "plt.style.use('ggplot')\n",
    "\n",
    "# 创建一个图形\n",
    "fig, ax = plt.subplots(figsize=(10, 5))\n",
    "\n",
    "# 绘制收盘价\n",
    "ax.plot(df['trade_date'], df['close'], label='收盘价', color='r')\n",
    "\n",
    "# 绘制开盘价\n",
    "ax.plot(df['trade_date'], df['open'], label='开盘价', color='g')\n",
    "\n",
    "# 绘制最高价和最低价之间的区域\n",
    "ax.fill_between(df['trade_date'], df['low'], df['high'], color='k', alpha=0.1)\n",
    "\n",
    "# 设置标题和标签\n",
    "ax.set_title('股票价格走势图')\n",
    "ax.set_xlabel('交易日期')\n",
    "ax.set_ylabel('价格')\n",
    "\n",
    "# 显示图例\n",
    "ax.legend()\n",
    "\n",
    "# 设置x轴日期格式\n",
    "ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
    "# 使用月份定位器\n",
    "ax.xaxis.set_major_locator(mdates.MonthLocator())\n",
    "\n",
    "# 自动调整子图参数, 使之填充整个图像区域（对于日期标签特别有用）\n",
    "fig.autofmt_xdate()\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:9: SyntaxWarning: invalid escape sequence '\\s'\n",
      "<>:9: SyntaxWarning: invalid escape sequence '\\s'\n",
      "C:\\Users\\lenovo\\AppData\\Local\\Temp\\ipykernel_41444\\389145620.py:9: SyntaxWarning: invalid escape sequence '\\s'\n",
      "  df = pd.read_csv(StringIO(data_str), sep='\\s+')\n",
      "C:\\Users\\lenovo\\AppData\\Local\\Temp\\ipykernel_41444\\389145620.py:18: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  ohlc.rename(columns={'vol': 'volume'}, inplace=True)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x575 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import mplfinance as mpf\n",
    "from io import StringIO\n",
    "\n",
    "\n",
    "def load_and_preprocess_data(data_str):\n",
    "    try:\n",
    "        # 将数据加载到 DataFrame 中\n",
    "        df = pd.read_csv(StringIO(data_str), sep='\\s+')\n",
    "        # 将 trade_date 列转换为日期类型\n",
    "        df['trade_date'] = pd.to_datetime(df['trade_date'], format='%Y%m%d')\n",
    "        # 将 trade_date 列设置为索引\n",
    "        df.set_index('trade_date', inplace=True)\n",
    "        # 对数据进行排序\n",
    "        df = df.sort_index()\n",
    "        # 选择需要的列\n",
    "        ohlc = df[['open', 'high', 'low', 'close', 'vol']]\n",
    "        ohlc.rename(columns={'vol': 'volume'}, inplace=True)\n",
    "        return ohlc\n",
    "    except Exception as e:\n",
    "        print(f\"数据处理过程中出现错误: {e}\")\n",
    "        return None\n",
    "\n",
    "\n",
    "def plot_candlestick_chart(ohlc):\n",
    "    if ohlc is not None:\n",
    "        # 自定义 K 线图样式\n",
    "        mpf_style = mpf.make_mpf_style(base_mpf_style='yahoo', rc={'font.size': 8})\n",
    "        # 绘制 K 线图\n",
    "        mpf.plot(ohlc, type='candle', volume=True, title='Stock Candlestick Chart', ylabel='Price',\n",
    "                 ylabel_lower='Volume', style=mpf_style)\n",
    "        # 显示图形\n",
    "        mpf.show()\n",
    "\n",
    "\n",
    "data = \"\"\"\n",
    "ts_code trade_date  close   open   high    low          vol  amount\n",
    "000002.SZ   20240101  25.2  25.0  25.5  24.8  15000000.0  3.75e+07\n",
    "000002.SZ   20240102  25.3  25.2  25.6  25.0  16000000.0  4.08e+07\n",
    "000002.SZ   20240103  25.1  25.3  25.4  24.9  14000000.0  3.53e+07\n",
    "000002.SZ   20240104  25.4  25.1  25.7  25.0  17000000.0  4.32e+07\n",
    "000002.SZ   20240105  25.5  25.4  25.8  25.2  18000000.0  4.59e+07\n",
    "000002.SZ   20240108  25.3  25.5  25.6  25.1  15500000.0  3.92e+07\n",
    "000002.SZ   20240109  25.6  25.3  25.9  25.2  17500000.0  4.48e+07\n",
    "000002.SZ   20240110  25.4  25.6  25.7  25.3  16500000.0  4.19e+07\n",
    "000002.SZ   20240111  25.7  25.4  26.0  25.3  18500000.0  4.71e+07\n",
    "000002.SZ   20240112  25.8  25.7  26.1  25.5  19000000.0  4.90e+07\n",
    "\"\"\"\n",
    "\n",
    "# 加载并预处理数据\n",
    "ohlc = load_and_preprocess_data(data)\n",
    "\n",
    "# 绘制 K 线图\n",
    "plot_candlestick_chart(ohlc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:9: SyntaxWarning: invalid escape sequence '\\s'\n",
      "<>:9: SyntaxWarning: invalid escape sequence '\\s'\n",
      "C:\\Users\\lenovo\\AppData\\Local\\Temp\\ipykernel_41444\\3045139778.py:9: SyntaxWarning: invalid escape sequence '\\s'\n",
      "  df = pd.read_csv(StringIO(data_str), sep='\\s+')\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1920x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from io import StringIO\n",
    "\n",
    "\n",
    "def load_data(data_str):\n",
    "    try:\n",
    "        # 从字符串读取数据到 DataFrame\n",
    "        df = pd.read_csv(StringIO(data_str), sep='\\s+')\n",
    "        return df\n",
    "    except Exception as e:\n",
    "        print(f\"数据加载过程中出现错误: {e}\")\n",
    "        return None\n",
    "\n",
    "\n",
    "def plot_limit_prices(df):\n",
    "    if df is not None:\n",
    "        # 设置图片清晰度\n",
    "        plt.rcParams['figure.dpi'] = 300\n",
    "        # 设置中文字体\n",
    "        plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "        # 解决负号显示问题\n",
    "        plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "        # 绘制涨跌停价格柱状图\n",
    "        x = range(len(df['ts_code']))\n",
    "        width = 0.35\n",
    "\n",
    "        fig, ax = plt.subplots()\n",
    "        # 设置不同颜色\n",
    "        rects1 = ax.bar([i - width / 2 for i in x], df['up_limit'], width, label='涨停价', color='red')\n",
    "        rects2 = ax.bar([i + width / 2 for i in x], df['down_limit'], width, label='跌停价', color='green')\n",
    "\n",
    "        # 添加数据标签\n",
    "        def autolabel(rects):\n",
    "            for rect in rects:\n",
    "                height = rect.get_height()\n",
    "                ax.annotate('{:.2f}'.format(height),\n",
    "                            xy=(rect.get_x() + rect.get_width() / 2, height),\n",
    "                            xytext=(0, 3),  # 3 points vertical offset\n",
    "                            textcoords=\"offset points\",\n",
    "                            ha='center', va='bottom')\n",
    "\n",
    "        autolabel(rects1)\n",
    "        autolabel(rects2)\n",
    "\n",
    "        # 设置图形标题和坐标轴标签\n",
    "        ax.set_ylabel('价格')\n",
    "        ax.set_title('2024 年部分日期股票涨跌停价格')\n",
    "        ax.set_xticks(x)\n",
    "        ax.set_xticklabels(df['ts_code'], rotation=90)\n",
    "        ax.legend()\n",
    "\n",
    "        # 显示图形\n",
    "        plt.tight_layout()\n",
    "        plt.show()\n",
    "\n",
    "\n",
    "\n",
    "data = \"\"\"\n",
    "trade_date    ts_code  up_limit  down_limit\n",
    "20240101  000001.SZ     16.08       13.12\n",
    "20240101  000002.SZ     32.12       26.38\n",
    "20240101  000004.SZ     26.21       21.42\n",
    "20240101  000005.SZ      3.61        2.97\n",
    "20240101  000006.SZ      6.32        5.16\n",
    "20240102  000007.SZ      7.92        6.52\n",
    "20240102  000008.SZ      4.41        3.62\n",
    "20240102  000009.SZ      6.54        5.34\n",
    "20240102  000010.SZ      3.63        3.26\n",
    "20240102  000011.SZ     10.78        8.86\n",
    "20240103  000012.SZ      5.32        4.36\n",
    "20240103  000014.SZ     11.18        9.12\n",
    "20240103  000016.SZ      4.93        4.02\n",
    "20240103  000017.SZ      5.31        4.33\n",
    "20240103  000018.SZ      1.48        1.34\n",
    "20240104  000019.SZ      8.26        6.76\n",
    "20240104  000020.SZ     12.42        10.18\n",
    "20240104  000021.SZ      9.48        7.76\n",
    "20240104  000023.SZ     14.86       12.16\n",
    "20240104  000025.SZ     23.38       19.12\n",
    "20240105  000026.SZ      8.82        7.22\n",
    "\"\"\"\n",
    "\n",
    "# 加载数据\n",
    "df = load_data(data)\n",
    "\n",
    "# 绘制图表\n",
    "plot_limit_prices(df)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
